User library service expectations in health science vs. other settings: a LibQUAL+® Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To explore how the library service expectations and perceptions of users might differ across health-related libraries as against major research libraries not operating in a medical context; to determine whether users of medical libraries demand better library service quality, because the inability of users to access needed literature promptly may lead to a patient who cannot be properly diagnosed, or a diagnosis that cannot be properly treated. METHODOLOGY: We compared LibQUAL+ total and subscale scores across three groups of US, Canadian and British libraries for this purpose. RESULTS: Anticipated differences in expectations for health as other library settings did not emerge. CONCLUSIONS: The expectations and perceptions are similar across different types of health science library settings, hospital and academic, and across other general research libraries.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.001 | 0.019 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it